#133 Truman State (8-11)

avg: 981.98  •  sd: 83.04  •  top 16/20: 0%

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# Opponent Result Game Rating Status Date Event
113 Saint Louis Win 7-6 1256.28 Feb 17th Dust Bowl 2024
124 Arkansas Loss 3-6 525.08 Feb 17th Dust Bowl 2024
77 Missouri Loss 5-15 768.96 Feb 17th Dust Bowl 2024
177 Missouri State Loss 5-6 557.97 Feb 17th Dust Bowl 2024
42 Texas-Dallas** Loss 0-11 1079.92 Ignored Feb 17th Dust Bowl 2024
96 Iowa State Loss 7-10 863.84 Feb 18th Dust Bowl 2024
113 Saint Louis Loss 7-9 851.94 Mar 2nd Midwest Throwdown 2024
237 Northwestern-B** Win 13-0 621.81 Ignored Mar 2nd Midwest Throwdown 2024
34 Washington University** Loss 2-11 1184.16 Ignored Mar 2nd Midwest Throwdown 2024
195 Washington University-B Win 6-5 636.38 Mar 2nd Midwest Throwdown 2024
35 St Olaf Win 5-4 1903.48 Mar 3rd Midwest Throwdown 2024
70 Northwestern Win 7-6 1544.28 Mar 3rd Midwest Throwdown 2024
34 Washington University** Loss 2-9 1184.16 Ignored Mar 3rd Midwest Throwdown 2024
127 Wisconsin-Eau Claire Win 7-4 1537.23 Mar 3rd Midwest Throwdown 2024
48 Colorado College** Loss 3-10 1013.36 Ignored Apr 13th South Central D III Womens Conferences 2024
223 Colorado College-B** Win 13-5 826.21 Ignored Apr 13th South Central D III Womens Conferences 2024
143 John Brown Win 9-8 1044.46 Apr 13th South Central D III Womens Conferences 2024
93 Rice Loss 3-11 681.27 Apr 13th South Central D III Womens Conferences 2024
66 Trinity Loss 3-13 856.11 Apr 14th South Central D III Womens Conferences 2024
**Blowout Eligible

FAQ

What is the uncertainty of the mean?
The uncertainty of the mean is equal to the standard deviation of the set of game ratings, divided by the square root of the number of games. We treated a team’s ranking as a normally distributed random variable, with the USAU ranking as the mean and the uncertainty of the ranking as the standard deviation
What's the algorithm again?
  1. Calculate uncertainy for USAU ranking averge
  2. Model ranking as a normal distribution around USAU averge with standard deviation equal to uncertainty
  3. Simulate seasons by drawing a rank for each team from their distribution. Note the teams in the top 16 (club) or top 20 (college)
  4. Sum the fractions for each region for how often each of it's teams appeared in the top 16 (club) or top 20 (college)
  5. Subtract one from each fraction for "autobids"
  6. Award remainings bids to the regions with the highest remaining fraction, subtracting one from the fraction each time a bid is awarded
Is there a longer explanation of all this?
There is an article on Ulitworld written by Scott Dunham and I that gives a little more context (though it probably was the thing that linked you here)